Corporate failure prediction: a study of public listed companies in Malaysia
Purpose - The objective of this paper is to develop a model that can predict financial distress amongst public listed companies in Malaysia using the logistic regression analysis. Design/methodology/approach - The logistic regression analysis used in this paper is geared towards developing a model that can predict financial distress amongst public listed companies in Malaysia. Findings - The results prove that five financial ratios have been found to be significant and useful for corporate failure prediction in Malaysia. The overall predictive accuracy is 91.5 percent and this demonstrates that the logistic regression analysis used is a reliable technique for financial distress prediction. In addition, the predictive accuracy of the model in this paper is higher than that of previous studies, which utilised discriminant analysis rather than the method adopted in this research. Originality/value - The economic crisis mostly began to affect Malaysia's economic standing in July 1997 causing many companies to fall into financial distress, as they were unable to cope with the unexpected downturn. A financial distress prediction model is therefore required to act as a predictor of Malaysian public listed companies' well-being prior to a financial crisis and to gauge the warning signals of the onset of a downturn in order to strategize their survival techniques during this phase. This study focuses on public listed companies in Malaysia, thus the model adopted is tailored to suit the given context.
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Volume (Year): 37 (2011)
Issue (Month): 6 (May)
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